TY - GEN
T1 - Brief Announcement
T2 - 39th Symposium on Principles of Distributed Computing, PODC 2020
AU - Ashkenazi, Yagel
AU - Gelles, Ran
AU - Leshem, Amir
N1 - Publisher Copyright: © 2020 ACM.
PY - 2020/7/31
Y1 - 2020/7/31
N2 - We introduce noisy beeping networks, where nodes have limited communication capabilities, namely, they can only emit energy or sense the channel for energy. Furthermore, imperfections may cause devices to malfunction with some fixed probability when sensing the channel, which amounts to deducing a noisy received transmission. Such noisy networks have implications for ultra-lightweight sensor networks and biological systems. We show how to compute tasks in a noise-resilient manner over noisy beeping networks of arbitrary structure. In particular, we transform any R-round algorithm that assumes a noiseless beeping network (of size n) into a noise-resilient version while incurring a multiplicative overhead of only O(log n + log R) in its round complexity, with high probability. We show that our coding is optimal for some (short) tasks, such as node-coloring of a clique. We further show how to simulate a large family of algorithms designed for distributed networks in the CONGEST(B) model over a noisy beeping network. The simulation succeeds with high probability and incurs an asymptotic multiplicative overhead of O(B · Δ · min(n, Δ2)) in the round complexity, where Δ is the maximum degree of the network. The overhead is tight for certain graphs, e.g., a clique. Further, this simulation implies a constant overhead coding for constant-degree networks.
AB - We introduce noisy beeping networks, where nodes have limited communication capabilities, namely, they can only emit energy or sense the channel for energy. Furthermore, imperfections may cause devices to malfunction with some fixed probability when sensing the channel, which amounts to deducing a noisy received transmission. Such noisy networks have implications for ultra-lightweight sensor networks and biological systems. We show how to compute tasks in a noise-resilient manner over noisy beeping networks of arbitrary structure. In particular, we transform any R-round algorithm that assumes a noiseless beeping network (of size n) into a noise-resilient version while incurring a multiplicative overhead of only O(log n + log R) in its round complexity, with high probability. We show that our coding is optimal for some (short) tasks, such as node-coloring of a clique. We further show how to simulate a large family of algorithms designed for distributed networks in the CONGEST(B) model over a noisy beeping network. The simulation succeeds with high probability and incurs an asymptotic multiplicative overhead of O(B · Δ · min(n, Δ2)) in the round complexity, where Δ is the maximum degree of the network. The overhead is tight for certain graphs, e.g., a clique. Further, this simulation implies a constant overhead coding for constant-degree networks.
KW - collision-detection
KW - error-correction in networks
KW - noise-resilience
UR - http://www.scopus.com/inward/record.url?scp=85090343648&partnerID=8YFLogxK
U2 - 10.1145/3382734.3405705
DO - 10.1145/3382734.3405705
M3 - منشور من مؤتمر
T3 - Proceedings of the Annual ACM Symposium on Principles of Distributed Computing
SP - 458
EP - 460
BT - PODC 2020 - Proceedings of the 39th Symposium on Principles of Distributed Computing
Y2 - 3 August 2020 through 7 August 2020
ER -